Specimens of an enameling steel were exposed at 57 sites of the National Air Sampling Network (NASN). Weight losses for one and two years of exposure at each site were determined. Available climatic data were collected and average relative humidities and average temperatures were calculated. Average levels of pollutants were determined from collected NASN data. The pollutants of interest were gaseous sulfur dioxide, total suspended particulate, sulfate in suspended particulate, and nitrate in suspended particulate.

Multiple linear regression and nonlinear curve fitting techniques were used to analyze the relationship between corrosion behavior of this steel and the collected atmospheric data. The resulting best empirical function has the form: cor=a0te[a1sula2/RH] where cor = depth of corrosion, μm t = time, years sul = average level of sulfate in suspended particulate (μg/m3) or average level of sulfur dioxide (μg/m3) RH = average relative humidity According to statistical analysis, differences in average temperature, average total suspended particulate, and average nitrate in suspended particulate caused insignificant changes in this steel's corrosion behavior. Sulfur dioxide was a significant variable only when sulfate in suspended particulate was not included in the regression analysis. The levels of these two pollutants generally change together from site to site (exhibit a high degree of covariance). Therefore, sulfate in suspended particulate may be a substitute variable for sulfur dioxide.